Showing 4,181 - 4,200 results of 7,164 for search 'NET information', query time: 0.12s Refine Results
  1. 4181

    Detection algorithm for wearing safety helmet under mine based on improved YOLOv5s by Yuanbin WANG, Sixiong WEI, Huaying WU, Yu DUAN, Meng LIU

    Published 2025-06-01
    “…By replacing the ordinary convolutional Conv in the YOLOv5s backbone network with ShuffleNetV2, the number of model parameters is greatly reduced and the recognition speed of the model is improved. …”
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  2. 4182

    Fully automatic fossa ovalis segmentation from computed tomography images using deep neural network with atlas-based localization by Gakuto Aoyama, Toru Tanaka, Yukiteru Masuda, Naoki Matsuki, Ryo Ishikawa, Masahiko Asami, Kiyohide Satoh, Takuya Sakaguchi

    Published 2025-01-01
    “…Methods: Our proposed method roughly crops CT images based on atlas information of the FO and heart chambers, and inputs the cropped CT images to a U-Net-based deep neural network (DNN) to segment the FO region. …”
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    Clopidogrel response predicts thromboembolic events associated with coil embolization of unruptured intracranial aneurysms: A prospective cohort study. by Eiji Higashi, Shoji Matsumoto, Ichiro Nakahara, Taketo Hatano, Akira Ishii, Nobutake Sadamasa, Tsuyoshi Ohta, Takuma Ishihara, Keisuke Tokunaga, Mitsushige Ando, Hideo Chihara, Konosuke Furuta, Tetsuya Hashimoto, Koji Tanaka, Kazutaka Sonoda, Junpei Koge, Wataru Takita, Takuro Hashikawa, Yusuke Funakoshi, Daisuke Kondo, Takahiko Kamata, Atsushi Tsujimoto, Takuya Matsushita, Hiroyuki Murai, Keitaro Matsuo, Takanari Kitazono, Junichi Kira

    Published 2021-01-01
    “…We evaluated preoperative clopidogrel response and patients' clinical information. We developed a patient-clinical-information model for thromboembolic event using multivariate analysis and compared its efficiency with that of patient-clinical-information plus preoperative clopidogrel response model. …”
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  5. 4185

    A Novel Approach for Visual Speech Recognition Using the Partition-Time Masking and Swin Transformer 3D Convolutional Model by Xiangliang Zhang, Yu Hu, Xiangzhi Liu, Yu Gu, Tong Li, Jibin Yin, Tao Liu

    Published 2025-04-01
    “…Visual speech recognition is a technology that relies on visual information, offering unique advantages in noisy environments or when communicating with individuals with speech impairments. …”
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    PC3D-YOLO: An Enhanced Multi-Scale Network for Crack Detection in Precast Concrete Components by Zichun Kang, Kedi Gu, Andrew Yin Hu, Haonan Du, Qingyang Gu, Yang Jiang, Wenxia Gan

    Published 2025-06-01
    “…Our methodology involves three key innovations: (1) the Multi-Dilation Spatial-Channel Fusion with Shuffling (MSFS) module, employing dilated convolutions and channel shuffling to enable global feature fusion, replaces the C3K2 bottleneck module to enhance long-distance dependency capture; (2) the AIFI_M2SA module substitutes the conventional SPPF to mitigate its restricted receptive field and information loss, incorporating multi-scale attention for improved near-far contextual integration; (3) a redesigned neck network (MSCD-Net) preserves rich contextual information across all feature scales. …”
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    SumGPT: A Multimodal Framework for Radiology Report Summarization to Improve Clinical Performance by Tipu Sultan, Mohammad Abu Tareq Rony, Mohammad Shariful Islam, Samah Alshathri, Walid El-Shafai

    Published 2025-01-01
    “…The SumGPT technique was evaluated against several baseline models, including BERT + EfficientNet, XLM-RoBERTa + ViT, T5+ CLIP, VisualGPT (GPT-2+ ViT), and others, using a dataset explicitly designed for this task. …”
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    An Online Paleoclimate Data Assimilation With a Deep Learning‐Based Network by Haohao Sun, Lili Lei, Zhengyu Liu, Liang Ning, Zhe‐Min Tan

    Published 2025-06-01
    “…Consistent results are obtained from the pseudoproxy experiments and the real proxy experiments. The more informative ensemble priors from the online PDA using NET enhance the reconstructions than the online PDA using LIM, and both outperform the offline PDA with randomly sampled climatological ensemble priors. …”
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